Network coding is known and is described e.g. in the following US published patent documents:
20030048855 20050152391 20060282677 20070280233 20050010675 20060224760 20070165673
Random projection as a method for reducing the dimensionality of a set of points in Euclidean space is known e.g. in:
Bingham, E. and Mannila, H. 2001, Random projection in dimensionality reduction: applications to image and text data. In Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (San Francisco, Calif., Aug. 26-29, 2001). KDD '01. ACM, New York, N.Y., 245-250; and
Santosh Vempala, The Random Projection Method, American Mathematical Society, 2004.
The following references describe technologies related to the field of the present invention:                1. Ye, Jieping and Janardan, Ravi and Li, Qi “GPCA: an efficient dimension reduction scheme for image compression and retrieval”. KDD '04: Proceedings of the tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2004.        2. W. B. Johnson and J. Lindenstrauss. “Extensions of Lipshitz mapping into Hilbert space”. In Conference in modern analysis and probability, volume 26 of Contemporary Mathematics, pages 189206. Amer. Math. Soc., 1984.        3. R. Hecht-Nielsen. “Context vectors: general purpose approximate meaning representations self-organized from raw data”. In J. M. Zurada, R. J. Marks II, and C. J. Robinson, editors, Computational Intelligence: Imitating Life, pages 4356. IEEE Press, 1994.        4. Shoulie Xie, Susanto Rahardja, and Zhengguo Li. “Wyner-Ziv Image Coding from Random Projections”. In IEEE International Conference on Multimedia and Expo, 2007.        
The disclosures of all publications and patent documents mentioned in the specification, and of the publications and patent documents cited therein directly or indirectly, are hereby incorporated by reference.